Grasshoppers, dementia, fake videos and more: ZHAW digital funds 7 new research projects
As part of the “Digital Futures Fund for Research”, ZHAW digital funds seven new research projects in the area of digital transformation.
Since 2020, ZHAW digital has been funding various projects as part of the "Digital Futures Fund" (DFF) funding program. From 2024, the successful program will be realigned: In the future, educational projects can be funded under the "Transformative Education Fund" and research projects under the "Digital Futures Fund for Research".
In this year's call for proposals for the "Digital Futures Fund for Research", seven research projects were able to impress with their innovative ideas and approaches and will each receive funding of CHF 20’000. What the research projects all have in common is that they respond to immediate challenges in the area of digital transformation with measures that can be implemented quickly.
Digital solutions for young and old
Nicole Zigan will explore the specific requirements and needs for the use of social assistance robots in care homes. These are to be used for people with dementia. Marion Pomey, on the other hand, is dedicated to children and young people in her project: she is researching how "well-being" can be created digitally in out-of-home care.
Many use cases for AI
Several projects deal with the use of artificial intelligence (AI) and show how versatile this technology can be. Matthias Nyfeler is developing a Deep Learning model to classify the sounds of grasshoppers (Orthoptera) using a smartphone. This is intended to advance efficient biodiversity monitoring through citizen science initiatives.
With their projects, Curtis Gautschi and Dominik Kunz are helping to drive forward the digital transformation at the ZHAW itself. Gautschi develops a Generative AI-based text quality assessment tool for Thesis Writer, a ZHAW-based dissertation writing support platform. And Kunz is developing and evaluating an AI-supported tool for the ZHAW to automate the work process for literature reviews.
Improve photos and detect fake videos
Helmut Grabner explores the question of what makes an image interesting and how to recognize good, attractive images. In his project, he is using computer vision methods to develop a web-based tool that can recognise and predict the most interesting image. The aim is to help users create images that appeal to their target groups.
Because we can encounter many (deep) fakes in photos and videos in our everyday digital lives, Patrick Giedemann's AI-based platform is designed to help fact-checkers recognise misinformation in videos.
You can find everything about the "Digital Futures Fund" and an overview of all projects funded or submitted to date on the ZHAW digital website.